Analysis of traffic inflow to a university campus in a developing country: A rescale range approach

ABSTRACT All over the world, there is an increasing enrolment level for university admissions in view of the ever-increasing benefits of eaming university degrees. Thus, the high population of students in many universities, coupled with a high number of vehicles has made traffic control a challenge to University traffic managers. In this paper, the method of Resca1e Range Analysis (RRA) was used to estimate the Hurst Exponent Value (HEV) for the traffic inflow through the main entrance gate of a university as a control measure. Data from a university in the developing countries was collected and analysed. The number of vehicles that entered consecutively per five minutes was observed between 07:00 and 19:00 over a 144 count and 17 independent cases constructed between adjacent cases. Rescale Range Algorithm platform is then used for the data, and coded in FORTRAN Language. With a case made up of 128 consecutive five-minute dependent traffic inflow records, a total of 3348 vehicles entered the university community within the studied period while the average number of vehicles inflow per hour was 279. Average number of vehicles that entered per five minutes was 24. No vehicle entered between 13:25 and 13:30. For all cases, the estimated HEV range between 0.5742 and 0.6955. The computed average HEV was 0.6303, the coefficient of fitness (R2) for all cases range between 0.9552 and 0.9787, while the computed average value was 0.9680. The HEV greater than 0.5 estimated for all cases is an indication of positive con-elation called Persistent. It expresses the fact that there are extended periods in which the traffic inflow to the university community deviated from the long term mean. This information is useful for vehicle garage design. For reliable estimates of the average HEV for design purposes, the study period should be extended to a whole week or an academic session.